Transcript Slide 1

Genesis of the use of RothC to model
soil organic carbon
Outline
• Composition of soil organic carbon – isolating
biologically important fractions
• Methodology for quantifying C allocation to
fractions
• Why attempt to understand allocation to fractions?
• Modelling soil carbon with RothC
• Substitution of conceptual with measureable C
pools in RothC
• MIR prediction of soil carbon fractions
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Composition of soil organic matter
• Crop residues on the soil
surface (SPR)
• Buried crop residues
(>2 mm) (BPR)
• Particulate organic matter
(2 mm – 0.05 mm) (POC)
• Humus (<0.05 mm)
(HumC)
• Resistant organic matter
(ROC)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Extent of decomposition
increases
Rate of decomposition
decreases
C/N/P ratio decreases
(become nutrient rich)
Dominated by charcoal
with variable properties
Biologically significant soil organic fractions
Particulate material
(POC)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Humus
(HumC)
Charcoal
(ROC)
Quantifying SOC allocation of SOC to fractions
Total soil organic carbon
Soil sieved to >2mm
Quadrat
collection
Surface plant
residue
carbon
Soil sieved to <2mm
Na saturate, disperse, sieve <53 µm
Density
fractionation
>53 µm fraction
Buried plant
residue
carbon
Density
fractionation
Particulate
organic
carbon
Humus = <53µm - Recalcitrant
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
<53 µm fraction
Humus +
recalcitrant
HF treatment,
UV-PO, & NMR
Recalcitrant
Charcoal C
25
(Mg C/ha)
Organic carbon in 0-10 cm layer
Variation in amount of C associated with soil
organic fractions
20
Surface plant residue C
(SPR)
15
Buried plant residue C
(BPR)
10
Particulate organic carbon
(POC)
Humus C (HumC)
5
Recalcitrant C
(ROC - charcoal)
0
Average for Hamilton
(long term pasture)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
30
SPR
BPR
POC
HumC
ROC
25
20
15
10
Hamilton
Hart
Yass
Pasture
Cropped
Pasture
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Urrbrae
Mix
Pasture/wheat
Pulse/wheat
Canola/wheat
W2PF
Perm Pasture
Arboretum
22P
11P
0P
Strat (HighN)
Strat (MedN)
NoTill (HighN)
NoTill (MedN)
32P
0
8P
5
1P
Organic C in 0-10 cm layer
(Mg C/ha)
Variation in amount of C associated with soil
organic fractions
Waikerie
Mix
Changes in total soil organic carbon with
time
Initiate
wheat/fallow
Total soil organic C
Conversion to
permanent
pasture
25
(g C kg-1 soil)
Soil organic carbon
30
20
15
10
5
0
10 y
18 y
0
10
20
15
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
30
50
40
33
43
60
70
Years
Importance of allocating C to soil organic
fractions
Initiate
wheat/fallow
TOC
Humus C
POC
ROC
Conversion to
permanent
pasture
25
(g C kg-1 soil)
Soil organic carbon
30
20
15
~30% less humus C
10
5
10 y
18 y
~800% more POC
0
0
10
20
15
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
30
50
40
33
43
60
70
Years
Vulnerability of soil carbon content to
variations in management practices
Initiate
wheat/fallow
Soil organic carbon
(g C kg-1 soil)
30
Conversion
to
wheat/fallow
Conversion
to pasture
25
20
TOC
Humus
POC
ROC
15
10
5
0
10 y
18 y
0
10
20
15
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
30
9y
50
40
33
43
60
52
70
Years
Importance of quantifying allocation of C to
soil organic fractions
Soil 2
20 g SOC kg-1 soil
Soil 1
20 g SOC kg-1 soil
10 g Char-C kg-1soil
2.5 g Char-C kg-1soil
25
15
10
5
Active C
Inert C
20
(g C kg-1 soil)
20
Soil Organic Carbon
(g C kg-1 soil)
Soil Organic Carbon
25
15
10
5
0
0
Time
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Active C
Inert C
Time
Summary SOC fractions
Total soil organic carbon
Soil sieved to >2mm
Quadrat
collection
Surface plant
residue
carbon
Soil sieved to <2mm
Na saturate, disperse, sieve <53 µm
Density
fractionation
>53 µm fraction
Buried plant
residue
carbon
Density
fractionation
Particulate
organic
carbon
Humus = <53µm - Recalcitrant
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
<53 µm fraction
Humus +
recalcitrant
HF treatment,
UV-PO, & NMR
Recalcitrant
Charcoal C
RothC Model (Version 26.3)
Plant
Inputs
DPM
Decomposition
RPM
CO2
BIO
Decomposition
HUM
Fire
IOM
CO2
BIO
HUM
Decomposition
Original configuration – monthly time step
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Roth C data requirements
• Monthly climate data: rainfall (mm), open pan evaporation
(mm), average monthly air temperature (°C)
• Soil clay content (% soil OD mass)
• Soil cover (vegetated or bare)
• Monthly plant residue additions (t C ha-1)
• Decomposability of plant residue additions
• Monthly manure additions (t C ha-1)
• Soil depth (cm)
• Initial amount of C contained in each pool
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
RothC model structure – partitioning residue inputs
into decomposable and resistant material
• All plant material entering the soil is partitioned into
DPM and RPM via DPM/RPM ratio
Management
DPM/RPM
Grassland and most agricultural crops
1.44
Unimproved grassland and scrub (savannas)
0.67
Deciduous and tropical woodlands
0.25
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
RothC model structure – amount of each
type of carbon decomposed
• The amount of carbon associated with each pool that
decomposes follows an exponential decay
Y  Y0 1 e-abckt 


a = the rate modifying factor for temperature
b = the plant retainment rate modifying factor
c = the rate modifying factor for soil water
k = the annual decomposition rate constant for a type of carbon
t = 0.0833, since k is based on a yearly decomposition rate.
Values of k for each SOC fraction (y-1)
BioF
0.66
BioS
0.66
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
DPM
10
RPM
0.15
Hum
0.02
RothC model structure – calculation of rate
constant modifying factors
• Temperature modifying factor (a)
1 e







106
tm  18.3







tm= average monthly temperature
Temperature modifying
factor (a)
47.9
a
7
6
5
4
3
2
1
0
-10
0
10
20
30
40
Monthly average temperature (°C)
• Plant retainment modifying factor (b)
b = 0.6 if soil is vegetated
b = 1.0 if soil is bare
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
RothC model structure – calculation of rate
constant modifying factors
Water present in the soil (mm)
• Soil water modifying factor – calculated based on top
soil moisture deficit (TSMD)
Saturation
Upper Limit
Total
porosity
TSMD
Lower Limit
Dry
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
RothC model structure – calculation of rate
constant modifying factors
• Calculation of maximum TSMD
MaxTSMD covered  (20.0 + 1.3 (%clay) - 0.01

in cm 

23


(%clay)2) depth








5
MaxTSMD bare   MaxTSMD covered
9 
• Calculation of accumulated TSMD over each time step
TSMDacc  TSMDinitial  rain  0.75PanEvap 


under the constraint that the accumulated TSMD can only vary
between 0 and MaxTSMD
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
RothC model structure – calculation of rate
constant modifying factors
• Calculation of the rate modifying factor (c)
if TSMDacc < 0.444 MaxTSMD then c=1.0
otherwise,
MaxTSMD  TSMDacc
 MaxTSMD  0.444MaxTSMD
c  0.2  1.0  0.2

1.0
c
0.2
0.444 MaxTSMD
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
MaxTSMD
RothC model structure – amount of each
type of carbon decomposed
• The amount of carbon associated with each pool that
decomposes follows an exponential decay
Y  Y0 1 e-abckt 


a = the rate modifying factor for temperature
b = the plant retainment rate modifying factor
c = the rate modifying factor for soil water
k = the annual decomposition rate constant for a type of carbon
t = 0.0833, since k is based on a yearly decomposition rate.
Values of k for each SOC fraction (y-1)
BioF
0.66
BioS
0.66
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
DPM
10
RPM
0.15
Hum
0.02
RothC Model (Version 26.3)
Plant
Inputs
DPM
Decomposition
RPM
CO2
BIO
Decomposition
HUM
Fire
IOM
CO2
BIO
HUM
Decomposition
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
RothC model structure – partitioning of
decomposition products
• Fraction decomposing organic matter that goes to CO2,
humus and biomass
• Partitioning to CO2 is defined by clay content
7
CO2 to (Bio+ Hum) ratio
6
5






0.0786 × %Clay
CO2
 1.67 1.85 1.6 e
Bio + Hum
4
3
2
1
0
CSIRO.







0
50
100
Clay
content
by mass)
Soil carbon
modelling
workshop(%
Adelaide
25-26/06/2008
Biomass + Humus partitioning
46% Bio
54% Hum













Amount of soil organic carbon
(Mg C/ha for 0-30 cm layer)
RothC output under constant inputs and
climate – to define equilibrium SOC
120
100
TOC
DPM
80
RPM
HUM
60
IOM
BIOF
40
BIOS
20
0
0
100
200
300
400
Years since start of simulation
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
500
Modelling the measurable
Plant
Inputs
DPM
Decomposition
RPM
CO2
BIO
Decomposition
HUM
Fire
IOM
CO2
BIO
HUM
Decomposition
RPM = POC
IOM = ROC (Charcoal C)
HUM = TOC – (POC + ROC)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Requirements for calibration
Soil samples
Representative composite soil samples collected at the
beginning and end of a period >10 years to a soil depth
of 30 cm.
Bulk density
Measured at time of sampling using soil core
weight/volume.
Crop yields
Yield of grain and pasture over each year to be modelled
and estimates of harvest index and root/shoot ratios
Management
Details of individual crops, rotations, fallow periods,
stubble burning and incorporation. If grazing occurred,
estimates of consumption and return from animals.
Climate
Details of average monthly air temperature, rainfall and
pan evaporation
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Model calibration and verification sites
Calibration Sites
Verification Sites
Brigalow
Tarlee
0
350
700
Kilometres
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Brigalow calibration site: influence of
modifying RPM decomposition constant (k)
RPM k=0.15
70
70
DPM
60
60
RPM
Soil C (Mg C/ha)
Soil C (Mg C/ha)
RPM k=0.30
50
40
30
20
IOM
40
BIO
30
Soil
POC
20
HUM
10
10
0
1982
HUM
50
1987
1992
1997
Year
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
0
1982
CHAR
TOC
1987
1992
Year
1997
Model Verification: (sites with archived soil
samples)
Wagga – wheat/pasture
Tamworth – wheat/fallow
50
40
20
0
1988 1990 1992 1994 1996 1998
Soil C (t/ha)
Soil C (t/ha)
60
40
30
Measured
POC
20
10
HUM
CHAR
0
1970
1980
Year
1990
2000
Year
TOC
Modeled
Salmon Gums – wheat/wheat
50
40
30
20
10
0
1979
Soil C (t/ha)
Soil C (t/ha)
Salmon Gums - wheat/ 3 pasture
1983
1987
1991
Year
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
50
40
30
20
10
0
1979
DPM
RPM
HUM
IOM
BIO
1983
1987
Year
1991
Soil
Model verification: (paired sites)
Kindon - pasture 15 y
Dunkerry South - crop
30
Soil C (t/ha)
Soil C (t/ha)
50
40
30
20
10
0
1986
20
10
0
1991
1996
2001
1967
1977
Year
1987
1997
Year
Measured
Modeled
POC
CHAR
DPM
HUM
BIO
HUM
TOC
RPM
IOM
Soil
• Is this result due poor model performance or poor pairing of the
sites?
• Did the sites start off similar or were there significant initial
differences in soil/plant/environmental properties?
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Quantifying SOC allocation of SOC to fractions
Total soil organic carbon
Soil sieved to >2mm
Quadrat
collection
Surface plant
residue
carbon
Soil sieved to <2mm
Na saturate, disperse, sieve <53 µm
Density
fractionation
>53 µm fraction
Buried plant
residue
carbon
Density
fractionation
Particulate
organic
carbon
Humus = <53µm - Recalcitrant
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
<53 µm fraction
Humus +
recalcitrant
HF treatment,
UV-PO, & NMR
Recalcitrant
Charcoal C
Predicting total organic carbon and its
allocation to SOC fractions using MIR
Intensity
Fourier Transform Infrared Spectrum
4
3
2
1
5000 4500 4000 3500 3000 2500 2000 1500 1000 500
Frequency (cm-1)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
• Dependence on soil
chemical properties
• Prediction of
allocation of carbon
to fractions via
calibration and PLS
Prediction of total organic carbon (TOC)
MIR predicted TOC (g C/kg soil)
177 Australian soils (all states) from varying depths within the
0-50 cm layer
n = 177
Range: 0.8 – 62.0 g C/kg
R2 = 0.94
Measured TOC (g C/kg soil)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Janik et al. 2007 Aust J Soil Res 45 73-81
Tasmanian soils project
MIR predicted LECO C (g/kg)
250
Sample specific calibration
200
y = 0.99x + 0.58
2
R = 0.99
150
100
Generic
calibration
50
y = 0.35x + 15.95
2
R = 0.86
0
0
50
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
100
150
200
LECO measured C (g/kg)
250
MIR prediction of particulate organic carbon
MIR predicted POC (g C/kg soil)
141 Australian soils (all states) from varying depths within the
0-50 cm layer
n = 141
Range: 0.2 – 16.8 g C/kg
R2 = 0.71
Variability in crop
residue type exits
Measured POC (g C/kg soil)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Janik et al. 2007 Aust J Soil Res 45 73-81
MIR prediction of charcoal C
MIR predicted Char C (g/kg)
121 Australian soils (all states) from varying depths within the
0-50 cm layer
n = 121
Range: 0.0 – 11.3 g C/kg
R2 = 0.86
Measured Char C (g/kg)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Janik et al. 2007 Aust J Soil Res 45 73-81
Summary
• Methodologies exist to quantify biologically
significant pools of carbon
• Understanding the dynamics of the pools allows
accurate interpretation of potential changes
• Substitution of measureable fractions for
conceptual pools in models is possible
• Rapid methods for predicting soil carbon
allocation to pools exist
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
CSIRO Land and Water
Jeff Baldock
Research Scientist
Phone: +61 8 8303 8537
Email: [email protected]
Web: http://www.clw.csiro.au/staff/BaldockJ/
Acknowledgements
Jan Skjemstad, Kris Broos, Evelyn Krull, Ryan
Farquharson, Steve Szarvas, Leonie Spouncer,
Athina Massis
Thank you
Contact Us
Phone: 1300 363 400 or +61 3 9545 2176
Email: [email protected] Web: www.csiro.au
Model Calibration
Brigalow South ws64 (RPM 0.15)
0-30 cm Soil C (t/ha)
70
Measured
POC
HUM
60
CHAR
50
TOC
40
Modeled
DPM
30
RPM
20
HUM
IOM
10
BIO
0
1982
Soil
1987
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Year 1992
1997
Defining soil C dynamics at Roseworthy, SA
under continuous wheat production
Average growing season (Apr-Oct) rainfall (mm)
338
Water limited potential grain yield (Mg/ha)
4.56
Grain yield used (Mg/ha) (85% water use efficiency)
3.88
Harvest index (Mg grain/Mg dry matter)
0.45
Total shoot dry matter production (Mg/ha)
8.62
Equilibrium conditions (model for 500 years)
Soil clay content
(%)
Amount of C in 0-30cm
layer (Mg C/ha)
C content of 0-10 cm
layer (%)
5
65
2.32
15
78
2.79
30
93
3.32
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Changes in soil C for different levels of
average grain yield
Soil organic C (0-10 cm layer)
(% of total soil mass)
8.0
7.0
0.5 T/ha
6.0
1 T/ha
5.0
2 T/ha
3 T/ha
4.0
4 T/ha
6 T/ha
3.0
8 T/ha
2.0
10 T/ha
1.0
0.0
0
100
200
300
Years since start of simulation
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
400
500
Changes in soil C for different levels of
average grain yield
Soil organic C (0-10 cm layer)
(% of total soil mass)
Shift 8.0
yield from 4 to 8 T grain/ha = 1.0 %C increase over 20 years
Shift yield from 4 to 6 T grain/ha = 0.4 %C increase over 20 years
7.0
0.5 T/ha
6.0
1 T/ha
5.0
2 T/ha
3 T/ha
4.0
4 T/ha
6 T/ha
3.0
8 T/ha
2.0
10 T/ha
1.0
0.0
0
5
10
15
Years since start of simulation
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
20
Composition of methodologically defined
SOC fractions
Particulate organic carbon (POC)
• Fragments of plant residues >53 µm (living and dead)
• Molecules sorbed to mineral particles >53 µm
• Large pieces of charcoal
Humus (HUM-C)
• Fragments <53 µm
• Molecules sorbed to particles <53 µm
Recalcitrant (ROC)
• Materials <53 µm that survive photo-oxidation
• Dominated by material with a charcoal-like chemical structure
• NMR to quantify char-C
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Spatial variation in soil charcoal and carbon
contents (0-10 cm layer)
TOC
180
160
Northern Boundary (m)
140
120
100
80
60
40
20
00
0
35
35
35
34
34
34
33
33
33
32
32
32
31
31
31
30
30
30
29
29
29
27
27
27
26
26
26
25
25
25
24
24
24
23
23
23
22
22
22
21
21
21
20
20
20
19
19
19
18
18
18
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17
17
16
16
16
15
15
15
14
14
14
13
13
13
12
12
12
11
11
11
10
10
10
9
9
9
8
8
8
7
7
7
6
6
6
5
5
5
4
4
4
3
3
3
2
2
2
1
1
1
25
50
75
Western Boundary (m)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
35
100
35
34
33
32
31
30
29
28
27
26
25
24
23
22
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
200
180
160
140
2.40
0.50
0.45
2.00
0.40
1.60
1.20
0.35
0.30
Northern Boundary (m)
200
Inert OC
120
100
80
60
0.25
40
0.80
0.20
0.40
0.00
0.15
0.10
20
00
0
35
35
35
34
34
34
33
33
33
32
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32
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31
31
30
30
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29
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8
8
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7
7
6
6
6
5
5
5
4
4
4
3
3
3
2
2
2
1
1
1
25
50
75
Western Boundary (m)
35
100
WF
WF
PPFW
PPFW
PPFW
PPFW
Perm. Past.
Contour bank
W O O(g) F
W O O(g) F
W O O(g) F
W O O(g) F
B Pe W
B Pe W
B Pe W
WPP
WPP
WPP
WW
WWPPPPP
WWPPPPP
WWPPPPP
WWPPPPP
WWPPPPP
WWPPPPP
WOF
WOF
WOF
W O(g) F
W O(g) F
W O(g) F
W Pe
W Pe
Perm. Past
Perm. Past
Predicting soil organic carbon contents
• Clearing of Brigalow bushland
Measured fractions
70
TOC
60
POC
C (t/ha)
HUM
50
CHAR
40
Modelled fractions
30
TOC
20
RPM
10
HUM
0
IOM
1982
1987
1992
Year
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
1997
Options for increasing soil carbon content
• Principal: increase inputs of carbon to the soil
• Maximise capture of CO2 by photosynthesis and addition of
carbon to soil
• Options
•
•
•
•
•
•
•
Maximise water use efficiency (kg total dry matter/mm water)
Maximise stubble retention
Introduction of perennial vegetation
Alternative crops - lower harvest index
Alternative pasture species – increased below ground allocation
Addition of offsite organic materials – diversion of waste streams
Green manure crops – legume based for N supply
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Options for increasing soil carbon content
• Constraints
• Soil type – protection and storage of carbon
• Local environmental conditions
– Dryland conditions – amount and distribution of rainfall
– Irrigation – maximise water use efficiency
• Economic considerations – alterations to existing systems must
remain profitable
• Social
• Options need to be tailored to local conditions and
farm business situation
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Defining inputs of organic carbon to soil – dryland
conditions
• Availability of water – amount and distribution of rainfall
imposes constraints on productivity and options
Mudgee, NSW
45
150
45
150
45
150
30
100
30
100
30
100
15
50
15
50
15
50
0
0
0
0
0
0
Month
of(mm)
the year
Rain
CSIRO. Soil carbon modelling
workshop
Adelaide(mm)
25-26/06/2008
Pan
Evaporation
Month
of(mm)
the year
Rain
Pan Evaporation (mm)
Nov
200
Sep
60
Jul
200
May
60
Mar
200
Jan
60
Nov
250
Sep
75
Jul
250
May
75
Mar
250
Jan
75
Nov
300
Sep
90
Jul
300
May
90
Mar
300
Month
of(mm)
the year
Rain
Pan Evaporation (mm)
Average monthly pan evaporation (mm)
Roseworthy, SA
90
Jan
Average monthly rainfall (mm)
Beverly, WA
Soil carbon sequestration situation
Evaluating potential C sequestration in soil
Potential
sequestration
Attainable
sequestration
Actual
sequestration
Defining
factors
Limiting
factors
Reducing
factors
Optimise input
and reduce
losses
Rainfall
Temperature
Light
Soil management
Plant species/crop selection
Residue management
Soil and nutrient losses
Inefficient water and nutrient use
Disrupted biology/disease
Add external
sources of
carbon
SOCactual
SOCattainable
SOCpotential
Stable soil organic carbon (e.g. t1/2  10 years)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Reactive surfaces
Depth
Bulk density
$$ for C sequestration – fact or fiction
• There is no doubt that soils could hold more carbon
• Challenge – increase soil C while maintaining economic
viability
• Options
• Perennial vegetation
• Regions with summer rainfall
• Portions of paddocks that give negative returns
• Reduce stocking, rotational grazing, green manure
• Optimise farm management to achieve 100% of water limited
potential yield
• External sources of carbon
• Under current C trading prices
• Difficult to justify managing for soil C on the basis of C trading
alone
• Do it for all the other benefits enhanced soil carbon gives
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Incorporation into a decision support
framework
MIR Analysis
SOC fractions
Clay
Climate data
Soil water limits
Soil C model with N
and P dynamics
C sequestration in
soils in response
to management
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Soil fertility and
fertiliser addition
rate calculators
Crop growth
Options for sequestering carbon
Photosynthesis
CO2
Mineralisation
Plant
production
Death/Harvest
Burning
Recalcitrant
organic C
(ROC)
Plant
residues
Increasing
extent of
decomposition
Particulate
organic C
Humus
organic C
Carbon sequestration options
1) increase C stored in plants – e.g. grow a forest
2) move more carbon into the recalcitrant pool
increase
CAdelaide
stored
in one or all soil components
CSIRO. 3)
Soil carbon
modelling workshop
25-26/06/2008
Soil animals
and microbes
What determines soil organic carbon
content?
Soil organic carbon
=
content
f
Inputs of
Losses of
,
organic carbon organic carbon
Inputs
• Net primary
productivity
• Addition of
waste organic
materials
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Losses
• Conversion of
organic C to
CO2 by
decomposition
Balance between inputs and outputs
25
(g C kg-1 soil)
Soil organic carbon
30
Inputs >> Outputs
20
Inputs > Outputs
15
Inputs = Outputs
Inputs < Outputs
10
Inputs << Outputs
5
0
0
20
40
60
80
100
120
140
Years
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Amount of carbon in the 0-10 cm layer
(Mg C/ ha)
Understanding the residue input requirements
to change soil carbon content
Amount of C required:
24 Mg C
50 Mg Dry Matter (DM)
90
80
70
60
50
48
40
1% SOC
Rate per year (no losses):
2% SOC
10 Mg DM/y
SOC
50% allocation below 3%
ground
SOC
equates to 5 Mg shoot4%DM/y
30
24
20
10
0
0.9
1
1.1
1.2
1.3
5% SOC
Rate per year (with 50% loss)
20 Mg DM/y (50% loss)
50% allocation below ground
10 Mg1.5shoot1.6DM/y1.7
1.4
Bulk density
(g/cm3)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Nutrients associated with soil carbon
Assumptions: C/N =10 and C/P=120)
140
BD = 1.0
1600
BD = 1.2
1400
BD = 1.4
1200
BD = 1.6
1000
800
600
400
Amount of P (kg/ha)
Amount of N (kg/ha)
1800
120
BD = 1.0
BD = 1.2
BD = 1.4
100
BD = 1.6
80
60
40
20
200
0
0
0.0 0.2 0.4 0.6 0.8 1.0
0.0 0.2 0.4 0.6 0.8 1.0
Change in soil carbon
(% of soil mass)
Change in soil carbon
(% of soil mass)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Variation in C/N ratio of different fractions of
soil organic matter
120
Upper boundry
C/N ratio
(weight basis)
100
Lower boundry
80
60
40
20
0
SPR
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Humus
POM
BPR
Type of organic matter
Minimum requirements for tracking soil
organic carbon for accounting purposes
1. Collection of a representative soil sample to a minimum
depth of 30 cm
2. An accurate estimate of the bulk density of the sample
3. An accurate measure of the organic carbon content of a
soil sample
For 0-30 cm soil with a bulk density of 1.0 Mg/m3 and
a carbon content of 1.0%
Bulk
Mass of
Carbon
Depth
x density x content = 30 Mg C/ha
Carbon =
(cm)
(g/cm3)
(Mg C/ha)
(%)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Dynamic nature of SOC and its fractions
32
(Mg C ha-1in 0-10 cm)
Amount of organic C
Irrigated Kikuyu pasture – Waite rotation trial
TOC
POC
Humus
ROC
24
16
8
0
1/6/98
6/2/99
14/10/99
20/6/00
Date of sample collection
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
25/2/01
Dynamic nature of SOC and its fractions
(Mg C ha-1 in 0-10 cm)
Amount of organic C
Dryland Pasture/Wheat/Wheat – Waite rotation trial
36
32
28
24
20
16
12
8
4
0
1/6/98
TOC
6/2/99
POC
Humus
14/10/99
20/6/00
Date of sample collection
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
ROC
25/2/01
Correcting soil carbon for management
induced changes in bulk density
Management induced compaction
Original soil surface
Original 30 cm depth
New 30 cm depth
Soil bulk density (Mg/m3)
1.1
1.2
1.3
1.4
Mass Soil 0-30 cm (Mg/ha)
3300
3600
3900
4200
Depth for equivalent mass (cm)
30.0
27.5
25.4
23.6
1% OC, no BD correction
33
36
39
42
1% OC, with BD correction
33
33
33
33
Organic C loading (Mg/ha)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Predicted equilibrium soil organic C contents for
3 regions in SA with different climate type
Clare
Roseworthy Waikerie
Growing season rain (mm)
491
338
170
Water limited potential grain yield (T/ha)
6.2
4.6
1.8
Grain yield (T/ha) (85% WUE)
5.3
3.9
1.5
Total shoot dry matter (T/ha)
11.7
8.6
3.4
Modelled amount of C in 0-30 cm (t C/ha)
98
78
41
Estimated %C in 0-10 cm soil layer
3.5
2.8
1.5
Equilibrium soil carbon content
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Take home messages
• Organic matter (carbon + other elements) is composed of a variety
of materials and improves soil productivity
• Different soils can hold different amounts of carbon
• Nature of soil minerals, depth and bulk density
• Balance between inputs and losses – goal is to maximise
production per mm available water
• Measuring changes in soil carbon requires careful consideration
• Options to increase carbon must be tailored to the local conditions
and economic considerations of the farmer
• Computer models exist to predict the impact of management on soil
carbon
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Tasmanian soils project
• Samples
• 154 soils collected from 0-10
cm layer of a diverse set of soil
x management combinations
• 30 measured values used to
derive the calibration
• All other samples predicted
from this calibration
• Range of Walkley-black C
contents
• 3.7 – 99.9 g C/kg soil
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
100
MIR predicted carbon content (g/kg)
• Objective: Prediction of total
organic carbon
80
60
40
20
y = 0.60x + 25.90
R2 = 0.37
0
0
50
100
150
-20
Measured carbon content
(g/kg)
Tasmanian soils project
250
120
Measured Walkley-Black C (g/kg)
MIR predicted LECO (g/kg)
y = 0.99x + 0.58
R2 = 0.99
200
150
100
50
y = 0.43x + 12.83
R2 = 0.61
100
80
60
40
20
0
0
0
100
200
300
Measured LECO C (g/kg)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
0
100
200
300
Measured LECO C (g/kg)
Functions of organic matter in soil
Biological functions
- energy for biological processes
- reservoir of nutrients
- contributes to resilience
Functions of SOM
Physical functions
Chemical functions
- improves structural stability
- cation exchange capacity
- influences water retention
- buffers changes in pH
- alters soil thermal properties
- complexes cations
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Distribution and turnover of organic carbon
in soil
0 cm
SOC
content
Proportion of
profile SOC
Relative
response time
High
30-50%
Rapid
Low
20-30%
Intermediate
to slow
Very
low
10-30%
Slow
10 cm
30 cm
100 cm
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Variation in soil organic carbon with depth
for different soils
Soil organic carbon content (% by weight)
0 1
0 1
0 1 2
0 1 2 3
0
2
4
Soil Depth (cm)
0
50
100
150
200
Red
brown
earths
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Grey
clays
Red
earths
Black
earths
Krasnozems
6
Significance of carbon in soils
World wide C pools (1015 g C)
• Atmosphere (CO2C)
780
• Living Biomass (plants, animals)
550
• Soil
0-1 m depth
1500
0-3 m depth
2300
1330
Houghton (2005)
Annual fluxes (1015 g C/yr)
Emissions
Responses
• Fossil fuel burning 6
• Land use change 2
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
• Atmospheric increase 3
• Oceanic uptake
2
• Other
3
Potential for soils to sequester C
Potential does exist to sequester C in soil
0 cm
10 cm
• SOC pool size: 1500 Pg
• Rapid cycling SOC: 500-750 Pg
• 1% increase in stored SOC/yr: 5 - 7.5 Pg/yr
30 cm
• CO2-C emissions: 8 Pg/yr
Issues
• Permanency of increase
• Native unmanaged soils
• Constraints on C inputs (biophysical,
economic, social)
100 cm
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Take home messages
• Soil organic matter provides many benefits to soil
• Different soils can hold different amounts of carbon
• Soil carbon represents the balance between additions and losses
• Soil carbon is composed of a variety of materials
• Understanding soil carbon composition allows more accurate
assessment of management impacts
• Measuring changes in soil carbon requires careful consideration
• Computer models exist to predict the impact of management on soil
carbon
• Options to improve soil carbon and productivity need to be tailored
to local conditions
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Understanding the residue input requirements
to change soil carbon content
Amount of carbon in the 0-10 cm layer
(Mg C/ ha)
Amount of C required:
14 Mg C
28 Mg90Dry Matter (DM)
80
Rate per
70year (no losses):
5.6 Mg
60 DM/y
50% allocation
below ground
50
2.8 Mg shoot DM/y
1% SOC
2% SOC
3% SOC
40
28
30year (with 50% loss)
Rate per
20 DM/y (50% loss)
11.2 Mg
50% allocation
below ground
10
5.6 Mg0 shoot DM/y
0.9
1
1.1
1.2
5% SOC
14
1.3
1.4
Bulk density
(g/cm3)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
4% SOC
1.5
1.6
1.7
Soil organic carbon content: influence of
management
• Defining the influence of management practices on soil
organic carbon is difficult
• Different types of organic C respond at different rates
• POC - years to decades
• Humus – decades to centuries
• Charcoal – centuries to millennia
• Other factors may be more influential in some years than
management (e.g. rainfall)
• Spatial variability and within year temporal variability
• Use of computer simulation models offers a way to
estimate likely outcomes quickly
• example soil carbon model: RothC
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Changes in soil C for different climates at a
constant wheat grain yield
Average grain yield of 4 T/ha
Soil organic C (0-10 cm layer)
(% of total soil mass)
4.0
3.0
2.0
Clare
Roseworthy
Waikerie
1.0
0.0
0
100
200
300
Years since start of simulation
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
400
500
Nutrients associated with soil carbon
Assumptions: C/N =10 and C/P=120)
140
BD = 1.0
1600
BD = 1.2
1400
BD = 1.4
1200
BD = 1.6
1000
800
600
400
Amount of P (kg/ha)
Amount of N (kg/ha)
1800
120
BD = 1.0
BD = 1.2
BD = 1.4
100
BD = 1.6
80
60
40
20
200
0
0
0.0 0.2 0.4 0.6 0.8 1.0
0.0 0.2 0.4 0.6 0.8 1.0
Change in soil carbon
(% of soil mass)
Change in soil carbon
(% of soil mass)
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Significance of carbon in soils
•World wide C pools (1015 g C)
• Atmosphere (CO2C)
• Living Biomass (plants, animals)
• Soil
0-1 m depth
0-3 m depth
780
550
1330
1500
2300
Houghton (2005)
•Annual fluxes (1015 g C/yr)
•Emissions
•Responses
• Fossil fuel burning 6
• Land use change 2
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
• Atmospheric increase 3
• Oceanic uptake
2
• Other
3
Cation exchange capacity
(meq/100g C)
Chemical function: Cation exchange
capacity
600
500
400
300
200
POM
Humus
100
Recalitrant
0
4
5
6
7
Soil pH
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
8
9
Questions remaining – from an organic
matter perspective
• What is the capacity of soils to store organic matter
(carbon and nutrients)?
• How much of the carbon and nutrients stored in soil
organic matter can be made available to microbes and
plants?
• What are the potential effects of alternative and new
management options on organic matter levels?
• Further quantification of the role of soil organic fractions
is required to extend the range of soil types and
environments examined.
• What is the role of external sources of organic matter and
do their influences persist?
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Significance of carbon in soils
•World wide C pools (1015 g C)
• Soil
• Atmosphere (CO2)
• Living Biomass (plants, animals)
Soil in Australia
1500
720
560
30
World fluxes (1015 g C/year)
Fossil
Vegetation
Missing
Atmospheric
Ocean
+ Uptake + Sink
Fuel + Destruction =
Increase
5
1.8
2.2
3
1.6
0.1% increase in soil organic C = 1.5
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Adding charcoal to soil : the Terra Preta
phenomenon
Terra
Preta
• High soil organic carbon – significant charcoal
• High P contents – 200–400 mg P/kg
• Higher cation exchange capacity
• Higher pH and base saturation
CSIRO. Soil carbon modelling workshop Adelaide 25-26/06/2008
Oxisol